Search

Multivalvular heart disease (MVD) implies the presence of concomitant valvular lesions on two or more heart valves. This condition has become common in the few last years, mostly due to population aging. Every combination of valvular lesions uniquely redefines the hemodynamics of a patient. Over time, this may lead to alterations in left ventricle (LV) dimensions, shape and, eventually, function. Since most of the echocardiographic parameters routinely used in the valvular assessment have been developed in the context of single valve disease and are frequently flow- and load-dependent, their indiscriminate use in the context of MVD can potentially lead to errors in judging lesion severity. Moreover, the combination of non-severe lesions may still cause severe hemodynamic consequences, and thereby systolic dysfunction. This review aims to discuss the most frequent combinations of MVD and their echocardiographic caveats, while addressing the opportunities for a multimodality assessment to achieve a better understanding and treatment of these patients.

Proper tricuspid valve (TV) function is essential to unidirectional blood flow through the right side of the heart. Alterations to the tricuspid valvular components, such as the TV annulus, may lead to functional tricuspid regurgitation (FTR), where the valve is unable to prevent undesired backflow of blood from the right ventricle into the right atrium during systole. Various treatment options are currently available for FTR; however, research for the tricuspid heart valve, functional tricuspid regurgitation, and the relevant treatment methodologies are limited due to the pervasive expectation among cardiac surgeons and cardiologists that FTR will naturally regress after repair of left-sided heart valve lesions. Recent studies have focused on (i) understanding the function of the TV and the initiation or progression of FTR using both in-vivo and in-vitro methods, (ii) quantifying the biomechanical properties of the tricuspid valve apparatus as well as its surrounding heart tissue, and (iii) performing computational modeling of the TV to provide new insight into its biomechanical and physiological function. This review paper focuses on these advances and summarizes recent research relevant to the TV within the scope of FTR. Moreover, this review also provides future perspectives and extensions critical to enhancing the current understanding of the functioning and remodeling tricuspid valve in both the healthy and pathophysiological states.

Severe aortic stenosis (AS) is the most common valvular heart disease with a prevalence rate of more than 4% in 75-year-old people or older. Similarly, cardiac amyloidosis (CA), especially “wild-type transthyretin” (wTTR), has shown a prevalence rate ranging from 22% to 25% in people older than 80 years. The detection of the concomitant presence of CA and AS is challenging primarily because of the similar type of changes in the left ventricle caused by AS and CA, which share some morphological characteristics. The aim of this review is to identify the imaging triggers in order to recognize occult wtATTR-CA in patients with AS, clarifying the crucial step of the diagnostic process. Multimodality imaging methods such as echocardiography, cardiac magnetic resonance, cardiac computed tomography, and DPD scintigraphy will be analyzed as part of the available diagnostic workup to identify wtATTR-CA early in patients with AS.

Structural and functional abnormalities of coronary microvasculature are highly prevalent in several clinical settings and often associated with worse clinical outcomes. Therefore, there is a growing interest in the detection and treatment of this, often overlooked, disease. Coronary angiography allows the assessment of the Coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR). However, the measurement of these parameters is not always feasible because of limited technical availability and the need for a cardiac catheterization with a small but real risk of potential complications. Recent advances in non-invasive imaging techniques allow the assessment of coronary microvascular function with good accuracy and reproducibility. The objective of this review is to discuss the strengths and weaknesses of alternative non-invasive approaches used in the diagnosis of coronary microvascular dysfunction (CMD), highlighting the most recent advances for each imaging modality. [ABSTRACT FROM AUTHOR]

Aims Psychological distress and changes in health-related quality of life (HRQoL) may occur after screening for disease. Reporting outcomes related to potential benefits and harms of screening is a key recommendation in the guidelines for reporting high-quality trials or interventions. However, no reviews have directly investigated outcomes related to psychological distress and/or changes in HRQoL following imaging assessment of cardiovascular risk and communication of cardiovascular findings to asymptomatic adults. A scoping review was conducted to map research on psychological distress and/or HRQoL following screening. Methods and results Six electronic databases (MEDLINE, PsychINFO, Social Work Abstracts, Psychology and Behavioural Sciences Collection, CINAHL, and EMBASE) were searched for articles that assessed psychological distress and/or HRQoL following screening. Two investigators independently screened titles and abstracts for all records retrieved using predefined criteria. Studies were conducted among active smokers, military personnel, athletes, post-menopausal women, and high-risk individuals. Seven constructs related to psychological distress and HRQoL appeared across 11 articles (randomized controlled trials, n = 4 and non-randomized studies, n = 7). Worry, depression, perceived stress, anxiety, and quality of life were most prominent. Multiple-item measures of psychological distress (e.g. Taylor Anxiety Score and Beck Depression Inventory) were used in 5/9 (56%) studies. Key findings on psychological distress and/or changes in HRQoL following screening were mixed. Conclusions Findings support the need for multiple-item measures with better psychometric properties to examine the psychological responses to screening results in future studies. Strategies to support individuals during and following vascular screening to maximise potential benefits of screening and minimize harms are discussed. [ABSTRACT FROM AUTHOR]

Cardiovascular disease is a deadly global health crisis that carries a substantial financial burden. Innovative treatment and management of cardiovascular disease straddles medicine, personalized hemodynamic modeling, machine learning, and modern imaging to help improve patient outcomes and reduce the economic impact. Hemodynamic modeling offers a non-invasive method to provide clinicians with new pre- and post- procedural metrics and aid in the selection of treatment options. Medical imaging is an integral part in clinical workflows for understanding and managing cardiac disease and interventions. Coupling machine learning with modeling, and cardiovascular imaging, provides faster modeling, improved data fidelity, and an enhanced understanding and earlier detection of cardiovascular anomalies, leading to the development of patient-specific diagnostic and predictive tools for characterizing and assessing cardiovascular outcomes. Herein, we provide a scoping review of translational hemodynamic modeling, medical imaging, and machine learning and their applications to cardiovascular interventions. We particularly focus on providing an intuitive understanding of each of these approaches and their ability to support decision making during important clinical milestones. [ABSTRACT FROM AUTHOR]

Endomyocardial biopsy (EMB) is an invasive procedure originally developed for the monitoring of heart transplant rejection. Over the year, this procedure has gained a fundamental complementary role in the diagnostic work-up of several cardiac disorders, including cardiomyopathies, myocarditis, drug-related cardiotoxicity, amyloidosis, other infiltrative and storage disorders, and cardiac tumours. Major advances in EMB equipment and techniques for histological analysis have significantly improved diagnostic accuracy of EMB. In recent years, advanced imaging modalities such as echocardiography with three-dimensional and myocardial strain analysis, cardiac magnetic resonance and bone scintigraphy have transformed the non-invasive approach to diagnosis and prognostic stratification of several cardiac diseases. Therefore, it emerges the need to re-define the current role of EMB for diagnostic work-up and management of cardiovascular diseases. The aim of this review is to summarize current knowledge on EMB in light of the most recent evidences and to discuss current indications, including challenging scenarios encountered in clinical practice. [ABSTRACT FROM AUTHOR]

Background and Objectives: The heart is the organ with the highest metabolic demand in the body, and it relies on high ATP turnover and efficient energy substrate utilisation in order to function normally. The derangement of myocardial energetics may lead to abnormalities in cardiac metabolism, which herald the symptoms of heart failure (HF). In addition, phosphorus magnetic resonance spectroscopy (31P MRS) is the only available non-invasive method that allows clinicians and researchers to evaluate the myocardial metabolic state in vivo. This review summarises the importance of myocardial energetics and provides a systematic review of all the available research studies utilising 31P MRS to evaluate patients with a range of cardiac pathologies. Materials and Methods: We have performed a systematic review of all available studies that used 31P MRS for the investigation of myocardial energetics in cardiovascular disease. Results: A systematic search of the Medline database, the Cochrane library, and Web of Science yielded 1092 results, out of which 62 studies were included in the systematic review. The 31P MRS has been used in numerous studies and has demonstrated that impaired myocardial energetics is often the beginning of pathological processes in several cardiac pathologies. Conclusions: The 31P MRS has become a valuable tool in the understanding of myocardial metabolic changes and their impact on the diagnosis, risk stratification, and prognosis of patients with cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Patients presenting with chest pain and related symptoms account for over 6 million emergency department (ED) visits in the United States annually. However, less than 5% of these patients are ultimately diagnosed with acute coronary syndrome (ACS). ED clinicians face the diagnostic challenge of promptly identifying and treating these high-risk patients amidst the overwhelming majority of lower-risk patients for whom further testing and/or treatment is either unnecessary or non-urgent. To assist with and expedite risk stratification and decision-making in this challenging clinical scenario, diagnostic tools like clinical risk scores and high-sensitivity serum biomarkers have been incorporated into care algorithms within the ED. In this narrative review, we discuss how these tools impact the appropriate use of cardiovascular imaging in the initial assessment of patients presenting to the ED with possible ACS. [ABSTRACT FROM AUTHOR]

Abstract Background Measurement of cardiac structure and function from images (e.g. volumes, mass and derived parameters such as left ventricular (LV) ejection fraction [LVEF]) guides care for millions. This is best assessed using cardiovascular magnetic resonance (CMR), but image analysis is currently performed by individual clinicians, which introduces error. We sought to develop a machine learning algorithm for volumetric analysis of CMR images with demonstrably better precision than human analysis. Methods A fully automated machine learning algorithm was trained on 1923 scans (10 scanner models, 13 institutions, 9 clinical conditions, 60,000 contours) and used to segment the LV blood volume and myocardium. Performance was quantified by measuring precision on an independent multi-site validation dataset with multiple pathologies with n = 109 patients, scanned twice. This dataset was augmented with a further 1277 patients scanned as part of routine clinical care to allow qualitative assessment of generalization ability by identifying mis-segmentations. Machine learning algorithm (‘machine’) performance was compared to three clinicians (‘human’) and a commercial tool (cvi42, Circle Cardiovascular Imaging). Findings Machine analysis was quicker (20 s per patient) than human (13 min). Overall machine mis-segmentation rate was 1 in 479 images for the combined dataset, occurring mostly in rare pathologies not encountered in training. Without correcting these mis-segmentations, machine analysis had superior precision to three clinicians (e.g. scan-rescan coefficients of variation of human vs machine: LVEF 6.0% vs 4.2%, LV mass 4.8% vs. 3.6%; both P

Abstract Background Infective endocarditis (IE) is a complex disease for which the European Society of Cardiology guideline recommends a dedicated multidisciplinary endocarditis team (ET) approach since 2015. It is currently unknown whether this ET approach is beneficial compared to a classic heart team approach including bedside consultation by an infectious disease specialist in Western Europe. Methods This retrospective single centre, observational cohort study was conducted at the Radboudumc, a tertiary referral centre in the Netherlands. Consecutive patients treated for IE were included from September 2017 to September 2018 before implementation of a dedicated ET and from May 2019 to May 2020 afterwards. Results In total, 90 IE patients (45 patients before and 45 patients after the implementation of the ET) were included. No significant differences were found in diagnostic workup, surgical treatment (surgery performed 69% vs. 71%, p = 0.82), time to surgery because of an urgent indication (median 4 vs. 6 days, p = 0.82), in-hospital complications (53% vs. 67%, p = 0.20), and 6-month mortality (11% vs. 13%, p = 0.75) between IE patients treated before and after the implementation of the ET. Conclusion Formalization of the recommended multidisciplinary endocarditis team might not significantly improve the complication rate nor the short term outcome.

Tetralogy of Fallot (TOF) is the most common complex congenital heart disease with long-term survivors, demanding serial monitoring of the possible complications that can be encountered from the diagnosis to long-term follow-up. Cardiovascular imaging is key in the diagnosis and serial assessment of TOF patients, guiding patients’ management and providing prognostic information. Thorough knowledge of the pathophysiology and expected sequalae in TOF, as well as the advantages and limitations of different non-invasive imaging modalities that can be used for diagnosis and follow-up, is the key to ensuring optimal management of patients with TOF. The aim of this manuscript is to provide a comprehensive overview of the role of each modality and common protocols used in clinical practice in the assessment of TOF patients.

ObjectivesThis study aimed to evaluate and compare the diagnostic accuracy of machine learning (ML)- fractional flow reserve (FFR) based on optical coherence tomography (OCT) with wire-based FFR irrespective of the coronary territory.BackgroundML techniques for assessing hemodynamics features including FFR in coronary artery disease have been developed based on various imaging modalities. However, there is no study using OCT-based ML models for all coronary artery territories.MethodsOCT and FFR data were obtained for 356 individual coronary lesions in 130 patients. The training and testing groups were divided in a ratio of 4:1. The ML-FFR was derived for the testing group and compared with the wire-based FFR in terms of the diagnosis of ischemia (FFR ≤ 0.80).ResultsThe mean age of the subjects was 62.6 years. The numbers of the left anterior descending, left circumflex, and right coronary arteries were 130 (36.5%), 110 (30.9%), and 116 (32.6%), respectively. Using seven major features, the ML-FFR showed strong correlation (r = 0.8782, P < 0.001) with the wire-based FFR. The ML-FFR predicted wire-based FFR ≤ 0.80 in the test set with sensitivity of 98.3%, specificity of 61.5%, and overall accuracy of 91.7% (area under the curve: 0.948). External validation showed good correlation (r = 0.7884, P < 0.001) and accuracy of 83.2% (area under the curve: 0.912).ConclusionOCT-based ML-FFR showed good diagnostic performance in predicting FFR irrespective of the coronary territory. Because the study was a small-size study, the results should be warranted the performance in further large-scale research.

Women’s engagement in medicine, and more specifically cardiovascular imaging and cardiovascular MRI (CMR), has undergone a slow evolution over the past several decades. As a result, an increasing number of women have joined the cardiovascular imaging community to contribute their expertise. This collaborative work summarizes the barriers that women in cardiovascular imaging have overcome over the past several years, the positive interventions that have been implemented to better support women in the field of CMR, and the challenges that still remain, with a special emphasis on women physicians.

Introduction: Utilization of cardiac magnetic resonance imaging (CMRI) has been increasing year by year for the most cardiovascular diseases. In this paper, we documented a real-life experience of our center as a high-volume CMRI performing center. Methods: We have retrospectively analyzed the 100 patients who have undergone CMRI at our center during the last 1 year. All the preliminary diagnoses, specialty or subspecialty of referring physicians, patient characteristics and CMRI findings were analyzed. Results: In 87 of 100 scans, a gadolinium-based contrast agent was used and in none of these procedures neither complications nor adverse events related to the contrast agent has occurred. Among these 100 consecutive CMRIs were referred to by a clinical cardiologist, invasive cardiologists, heart failure specialist, cardiovascular imaging specialists, electrophysiologists, and other specialists. On referral from a clinical cardiologist, the CMRI findings were high consistency. In these patients, the biggest number of preliminary diagnoses belongs to hypertrophic cardiomyopathy. The most common MRI finding was reduced left ventricular ejection fraction. In 25 patients we observed extracardiac findings. Conclusion: CMRI is increasingly occurring in cardiovascular imaging and diagnosis of various cardiovascular diseases. CMRI not only produces high-resolution morphological images but also provides quantitative information on the severity of regurgitant or stenotic lesions in valvular diseases or cardiac shunts with the velocity and flow measurements. [ABSTRACT FROM AUTHOR]

Copyright of Die Radiologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Die Radiologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background Cancer therapy–related cardiac dysfunction (CTRCD) is a challenging and life-threatening complication of many chemotherapeutic regimens. CTRCD prevention, diagnosis, and therapy require both careful interdisciplinary assessment and management. For patients with CTRCD, current guidelines of the European Society of Cardiology (ESC) recommend an angiotensin-converting-enzyme inhibitor in combination with a beta-blocker. Recent studies indicate a beneficial effect of sacubitril/valsartan in this patient population. Case summary A 68-year-old female patient with a pleural epithelioid angiosarcoma developed heart failure with reduced ejection fraction and elevated serum biomarkers following doxorubicin treatment. After implementation of a recommended cardioprotective medical therapy including torasemide, ramipril, carvedilol, and spironolactone, the patient suffered two cardiac decompensations within 4 weeks after initiation of a paclitaxel regimen and pleural radiation therapy due to pain exacerbation. Despite a continuous application of the cardioprotective medical treatment regimen, no improvement of left-ventricular ejection fraction (LVEF) was detected in a 4-month follow up. Interestingly, after omitting ramipril and implementing low-dose sacubitril/valsartan (26/24 mg), we observed a decrease in serum biomarkers within 3 months as well as a significant improvement of LVEF within 6 months. After nearly 10 months of disease stabilization under paclitaxel, the patient suffered progressive cancer disease and deceased 1 week later after the initiation of a therapeutic attempt with pazopanib. Discussion This case report highlights the importance of interdisciplinary care in cancer patients as well as the promising role of (low-dose) sacubitril/valsartan in patients with CTRCD even in the setting of delayed initiation. [ABSTRACT FROM AUTHOR]

To determine if coronary artery calcium (CAC) scoring using computed tomography at 80 kilovolt-peak (kVp) and 70-kVp and tube voltage-adapted scoring-thresholds allow for accurate risk stratification as compared to the standard 120-kVp protocol. We prospectively included 170 patients who underwent standard CAC scanning at 120-kVp and 200 milliamperes and additional scans with 80-kVp and 70-kVp tube voltage with adapted tube current to normalize image noise across scans. Novel kVp-adapted thresholds were applied to calculate CAC scores from the low-kVp scans and were compared to those from standard 120-kVp scans by assessing risk reclassification rates and agreement using Kendall's rank correlation coefficients (Τb) for risk categories bounded by 0, 1, 100, and 400. Interreader reclassification rates for the 120-kVp scans were assessed. Agreement for risk classification obtained from 80-kVp and 70-kVp scans as compared to 120-kVp was good (Τb = 0.967 and 0.915, respectively; both p < 0.001) with reclassification rates of 7.1% and 17.2%, respectively, mostly towards a lower risk category. By comparison, the interreader reclassification rate was 4.1% (Τb = 0.980, p < 0.001). Reclassification rates were dependent on body mass index (BMI) with 7.1% and 13.6% reclassifications for the 80-kVp and 70-kVp scans, respectively, in patients with a BMI < 30 kg/m2 (n = 140), and 2.9% and 7.4%, respectively, in patients with a BMI < 25 kg/m2 (n = 68). Mean effective radiation dose from the 120-kVp, the 80-kVp, and 70-kVp scans was 0.54 ± 0.03, 0.42 ± 0.02, and 0.26 ± 0.02 millisieverts. CAC scoring with reduced tube voltage allows for accurate risk stratification if kVp-adapted thresholds for calculation of CAC scores are applied. ClinicalTrials.gov NCT03637231. [ABSTRACT FROM AUTHOR]

In this digital era, artificial intelligence (AI) is establishing a strong foothold in commercial industry and the field of technology. These effects are trickling into the healthcare industry, especially in the clinical arena of cardiology. Machine learning (ML) algorithms are making substantial progress in various subspecialties of cardiology. This will have a positive impact on patient care and move the field towards precision medicine. In this review article, we explore the progress of ML in cardiovascular imaging, electrophysiology, heart failure, and interventional cardiology. [ABSTRACT FROM AUTHOR]

Introduction: Pulmonary embolism is a common cause of cardiopulmonary mortality and morbidity worldwide. Survivors of acute pulmonary embolism may experience dyspnea, report reduced exercise capacity, or develop overt pulmonary hypertension. Clinicians must be alert for these phenomena and appreciate the modalities and investigations available for evaluation.Areas Covered: In this review, the current understanding of available contemporary imaging and physiologic modalities is discussed, based on available literature and professional society guidelines. The purpose of the review is to provide clinicians with an overview of these modalities, their strengths and disadvantages, and how and when these investigations can support the clinical work-up of patients post-pulmonary embolism.Expert Opinion: Echocardiography is a first test in symptomatic patients post-pulmonary embolism, with ventilation/perfusion scanning vital to determination of whether there is chronic residual emboli. The role of computed tomography and magnetic resonance in assessing the pulmonary arterial tree in post-pulmonary embolism patients is evolving. Functional testing, in particular cardiopulmonary exercise testing, is emerging as an important modality to quantify and determine cause of functional limitation. It is possible that future investigations of the post-pulmonary embolism recovery period will better inform treatment decisions for acute pulmonary embolism patients. [ABSTRACT FROM AUTHOR]

Objectives: This study evaluated the association between serum albumin levels and coronary artery calcification (CAC) progression in asymptomatic adults without hypoalbuminaemia at baseline., Design: Observational cohort study., Setting: Data from the Korea Initiatives on Coronary Artery Calcification (KOICA) which is a retrospective, single ethnicity, multicentre and observational registry were analysed., Participants: A total of 12 344 Korean adults with baseline albumin level of ≥3.5 g/dL (51.7±8.5 years; 84.3% male) were included. The median interscan period was 3.0 (2.0-4.8) years. All participants were stratified into three groups based on serum albumin tertile., Primary and Secondary Outcome Measures: Association of serum albumin with the risk of CAC progression was analysed using multivariate logistic regression models with adjustment of interscan period. CAC progression was defined as a square root (√) transformed difference between the baseline and follow-up coronary artery calcium score (CACS) (Δ√transformed CACS) of ≥2.5. Annualised Δ√transformed CACS was defined as Δ√transformed CACS divided by interscan period., Results: With increasing serum albumin tertiles, the annualised Δ√transformed CACS (I (lowest): 0.16 (0-1.24) vs II: 0 (0-1.09) vs III (highest): 0 (0-1.01)) and the incidence of CAC progression (I: 36.6% vs II: 31.3% vs III: 25.0%) were decreased despite higher prevalence of hypertension, diabetes and hyperlipidaemia (all p<0.05). Serum albumin levels were inversely related to the annualised Δ√transformed CACS and the risk of CAC progression among overall participants. After adjusting for age, sex, hypertension, diabetes, hyperlipidaemia, obesity, current smoking, alcohol consumption, serum creatinine levels, baseline CACS and interscan period, this inverse association between serum albumin levels (per-1 g/dL increase) and the risk of CAC progression was consistently observed, especially in baseline CACS of 1-10 (OR: 0.392, 95% CI: 0.234 to 0.658) and 11-100 (OR: 0.580, 95% CI: 0.381 to 0.883) (all p<0.05)., Conclusions: Serum albumin levels were inversely associated with the risk of CAC progression. This phenomenon was predominantly observed in CACS of 1-100 at baseline., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Hypertensive pregnancies are associated with an increased risk of cardiovascular and neurological diseases in the offspring during later life. However, less is known about the potential impact on multi-organ phenotypes in offspring before disease symptoms occur. The objective of this systematic review was to determine the associations of fetal exposure to maternal hypertensive pregnancy with multi-organ phenotypes across developmental stages., Methods and Results: Ovid MEDLINE, EMBASE, CENTRAL (Cochrane Central Register of Controlled Trials), WoS, Scopus, CINAHL, and ClinicalTrials.gov were systematically searched until February 2024. Records were independently screened by 2 authors. Studies reporting on the structure or function of the heart, blood vessels, brain, liver, and kidneys in offspring of hypertensive pregnancies compared with a normotensive control population were included. Risk of bias was assessed using the Newcastle-Ottawa Scale. Extracted data were presented using harvest plots. Seventy-three studies including 7091 offspring of hypertensive pregnancies and 42 164 controls were identified that met the inclusion criteria. Thirty-two studies were investigations in fetuses, 24 in neonates and infants, 12 in children, 2 in adolescents, and 3 in adults. Offspring of hypertensive pregnancies had structural and functional changes in the heart compared with controls in some studies across developmental stages. Offspring of hypertensive pregnancies also had smaller occipital and parietal vessels, higher aortic intima-media thickness, and lower retinal arteriolar-to-venular ratio. Some conflicting evidence existed for other phenotypical alterations., Conclusions: There is still inconsistent evidence of multi-organ structural and functional differences in offspring of hypertensive pregnancies. The evidence base could therefore be further strengthened through well-designed and conducted prospective studies., Registration Information: www.crd.york.ac.uk. Unique Identifier: CRD42023387550.

Noninvasive and invasive imaging modalities play important roles for the detection of patent foramen ovale (PFO). Transthoracic echocardiography or transcranial Doppler bubble study can be used for initial noninvasive PFO screening. For diagnostic confirmation, transesophageal echocardiography bubble study can be utilized, a semiinvasive confirmatory test that can directly visualize a PFO. In selective cases when the diagnosis is in doubt, PFO can be accurately diagnosed invasively with right heart catheterization. Understanding the advantages and limitations of each diagnostic option will help clinicians choose the appropriate test for patients presenting with a PFO-associated condition who may benefit from percutaneous device closure., Competing Interests: Disclosure This research was supported in whole or in part by HCA Healthcare, United States and/or an HCA Healthcare affiliated entity. The views expressed in this publication represent those of the authors and do not necessarily represent the official views of HCA Healthcare or any of its affiliated entities., (Published by Elsevier Inc.)

Background: Left ventricular end-diastolic pressure (LVEDP) is a key indicator of cardiac health. The gold-standard method of measuring LVEDP is invasive intra-cardiac catheterization. Echocardiography is used for non-invasive estimation of left ventricular (LV) filling pressures; however, correlation with invasive LVEDP is variable. We sought to use machine learning (ML) algorithms to predict elevated LVEDP (>20 mmHg) using clinical, echocardiographic, and biomarker parameters., Methods: We identified a cohort of 460 consecutive patients from the Cleveland Clinic, without atrial fibrillation or significant mitral valve disease who underwent transthoracic echocardiography within 24 hours of elective heart catheterization between January 2008 and October 2010. We included patients' clinical (e.g., heart rate), echocardiographic (e.g., E/e'), and biomarker [e.g., N-terminal brain natriuretic peptide (NT-proBNP)] profiles. We fit logistic regression (LR), random forest (RF), gradient boosting (GB), support vector machine (SVM), and K-nearest neighbors (KNN) algorithms in a 20-iteration train-validate-test workflow and measured performance using average area under the receiver operating characteristic curve (AUROC). We also predicted elevated tau (>45 ms), the gold-standard parameter for LV diastolic dysfunction, and performed multi-class classification of the patients' cardiac conditions. For each outcome, LR weights were used to identify clinically relevant variables., Results: ML algorithms predicted elevated LVEDP (>20 mmHg) with good performance [AUROC =0.761, 95% confidence interval (CI): 0.725-0.796]. ML models showed excellent performance predicting elevated tau (>45 ms) (AUROC =0.832, 95% CI: 0.700-0.964) and classifying cardiac conditions (AUROC =0.757-0.975). We identified several clinical variables [e.g., diastolic blood pressure, body mass index (BMI), heart rate, left atrial volume, mitral valve deceleration time, and NT-proBNP] relevant for LVEDP prediction., Conclusions: Our study shows ML approaches can robustly predict elevated LVEDP and tau. ML may assist in the clinical interpretation of echocardiographic data., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (https://cdt.amegroups.com/article/view/10.21037/cdt-24-128/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Background: Type 2 Diabetes (T2D) leads to cardiovascular remodeling, and heart failure has emerged as a major complication of T2D. There is a limited understanding of the impact of T2D on the right heart. This study aimed to assess subclinical right heart alterations and their contribution to aerobic exercise capacity (peak VO 2 ) in adults with T2D., Methods: Single center, prospective, case-control comparison of adults with and without T2D, and no prevalent cardiac disease. Comprehensive evaluation of the left and right heart was performed using transthoracic echocardiography and stress cardiovascular magnetic resonance. Cardiopulmonary exercise testing on a bicycle ergometer with expired gas analysis was performed to determine peak VO 2 . Between group comparison was adjusted for age, sex, race and body mass index using ANCOVA. Multivariable linear regression including key clinical and left heart variables, was undertaken in people with T2D to identify independent associations between measures of right ventricular (RV) structure and function with peak VO 2 ., Results: 340 people with T2D (median age 64 years, 62% male, mean HbA1c 7.3%) and 66 controls (median age 58 years, 58% male, mean HbA1c 5.5%) were included. T2D participants had markedly lower peak VO 2 (adjusted mean 20.3(95% CI: 19.8-20.9) vs. 23.3(22.2-24.5) mL/kg/min, P<0.001) than controls and had smaller left ventricular (LV) volumes and LV concentric remodeling. Those with T2D had smaller RV volumes (indexed RV end-diastolic volume: 84(82-86) vs. 100(96-104) mL/m, P<0.001) with evidence of hyperdynamic RV systolic function (global longitudinal strain: 26.3(25.8-26.8) vs. 23.5(22.5-24.5) %, P<0.001) and impaired RV relaxation (longitudinal peak early diastolic strain rate: 0.77(0.74-0.80) vs. 0.92(0.85-1.00) s -1 , P<0.001). Multivariable linear regression demonstrated that RV end-diastolic volume (β=-0.342, P=0.004) and RV cardiac output (β=0.296, P=0.001), but not LV parameters, were independent determinants of peak VO 2 ., Conclusions: In T2D, markers of RV remodeling are associated with aerobic exercise capacity, independent of left heart alterations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Competing interests The authors declare that they have no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Cardiovascular diseases (CVDs) are the major cause of mortality worldwide, emphasizing the critical need for timely and accurate diagnosis. Artificial intelligence (AI) and machine learning (ML) have become revolutionary tools in the healthcare system with significant potential for cardiovascular diagnosis and imaging. AI and ML techniques, including supervised and unsupervised learning, logistic regression, deep learning models, neural networks, and convolutional neural networks (CNNs), have significantly advanced cardiovascular imaging. Applications in echocardiography include left and right ventricular segmentation, ejection fraction measurement, and wall motion analysis. AI and ML hold substantial promise for revolutionizing cardiovascular imaging, demonstrating improvements in diagnostic accuracy and efficiency. This narrative review aims to explore the current applications, advantages, challenges, and future pathways of AI and ML in cardiovascular imaging, highlighting their impact on different imaging modalities and their integration into clinical practice., Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Cerdas et al.)

Objectives: To determine whether bisphosphonates and NF-κB ligand (RANKL) inhibitors delay coronary artery calcification (CAC)., Design: A systematic review was conducted., Data Sources: MEDLINE, EMBASE and CENTRAL., Eligibility Criteria: Longitudinal studies investigating CAC progression in adults (>18 years) taking either a bisphosphonate or denosumab compared with those who did not., Data Extraction and Synthesis: Study and participant characteristics, and primary outcome ( ∆ CAC from baseline to follow-up) were extracted. The Risk Of Bias In Non-Randomised Studies-of Interventions (ROBINS-I) and Risk-of-Bias Tool for Randomised Trials (RoB2) tools were used to assess the risk of bias for observational and randomised controlled trials (RCTs), respectively. Outcome measures were reported., Results: Four observational studies and one RCT (n=377) were included. Three studies solely reported the effect of bisphosphonates on ∆ CAC; one study (n=56) demonstrated a statistically significant CAC reduction in the intervention group (-372 mm 3 /year) compared with control (+159 mm 3 /year) (p<0.01). One study (n=14) demonstrated a difference in ∆ CAC between intervention (+880 mm 3 /year) versus control (+2220 mm 3 /year), however, no p value comparing groups was reported. One study (n=115) found no statistically significant difference between intervention and control.One study (n=42) exclusively investigated the effect of RANKL on ∆ CAC; there was a statistically significant reduction in CAC at 6-month follow-up between intervention (-133±124 modified Agatston unit (AU)) and control (+188±72 modified AU), p=0.03.One study (n=150) compared both bisphosphonates and denosumab to control and found no statistically significant difference between either intervention group and control over 24 months. Meta-analysis was not performed due to limited, heterogeneous studies., Conclusions: There is insufficient evidence supporting the correlation between bisphosphonate or RANKL inhibitor use and CAC progression. Further research is warranted., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Baseline cardiovascular assessment before the initiation of potentially cardiotoxic cancer therapies is a key component of cardio-oncology, aiming to reduce cardiovascular complications and morbidity in patients and survivors. Recent clinical practice guidelines provide both general and cancer therapy-specific recommendations for baseline cardiovascular toxicity risk assessment and management, including the use of dedicated risk scores, cardiovascular imaging, and biomarker testing. However, the value of such interventions in altering disease trajectories has not been established, with many recommendations based on expert opinion or Level of Evidence: C, studies with a potential for high risk of bias. Advances in understanding underlying mechanisms of cardiotoxicity and the increased availability of genetic and immunologic profiling present new opportunities for personalized risk assessment. This paper evaluates the existing evidence on cardiovascular care of cancer patients before cardiotoxic cancer therapy and highlights gaps in evidence and priorities for future research., Competing Interests: Dr Raisi-Estabragh recognizes the National Institute for Health and Care Research Integrated Academic Training program (CL-2021-19-00), which supports her academic clinical lectureship post and was also supported by a British Heart Foundation Clinical Research Training Fellowship (FS/17/81/33318). Dr Murphy is supported by the National Health and Medical Research Council and the National Heart Foundation. Dr Apperley is a National Institute of Health for Health and Care Research emeritus senior investigator and acknowledges the support of the National Institute for Health and Care Research Biomedical Research Centre at Imperial College London. Prof Manisty is supported directly and indirectly from the National Institute for Health and Care Research Biomedical Research Centres at University College London Hospitals and Barts Health NHS Trusts. Dr Ramalingam has received honorariums from AstraZeneca and Ferring Pharmaceuticals. Dr Lopez-Fernandez has received speaker fees from Philips, Janssen, Daichi-Sankyo, Myocardial Solutions, AstraZeneca, Beigene, Bayer, and Pfizer not related with the current work. Dr Reynolds has served on the Advisory Board of SAGA Diagnostics; has provided educational lectures for CMO Outfitters and MedScape; and has received institutional research funding from Bristol Myers Squibb. Dr Lin has received consulting fees and salary from TenSixteen Bio. Dr Apperley has contributed to advisory committees and Speakers Bureau for Incyte and Novartis; and has received research funding from Incyte and Pfizer. Dr Cheng has received speaker and advisory fees from Janssen, AbbVie, AstraZeneca, Lilly, Beigene, Kite, BMS, Roche, and GenMab. Dr Manisty serves as a speaker and advisor for Pfizer, Beigene, Biotronik, and Abbott St. Jude Medical; and is a cofounder of MycardiumAI. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2024 The Authors.)

Background: Immunoglobulin G4-related disease (IgG4-RD) is a fibroinflammatory condition characterized by IgG4-positive plasma cell infiltration that can affect multiple organs, including the cardiovascular system. The diagnosis of IgG4-RD relies on a combination of clinical, serological, radiological, and pathological findings. However, due to the varied and insidious clinical presentations, normal IgG4 levels in a significant percentage of patients, and frequent multi-organ involvement, imaging plays a crucial role in the diagnosis of IgG4-RD. The aim of study is to comprehensively examine the imaging findings in IgG4-related cardiovascular disease for accurate diagnosis and appropriate treatment., Methods: A systematic search was conducted across electronic databases, PubMed, Scopus, and Web of Sciences, until 1 September 2023, following PRISMA guidelines by searching major databases for studies reporting detailed cardiovascular imaging findings in IgG4-RD., Results: The search yielded 68 studies (60 case reports, 5 case series, 2 cross-sectional, 1 case-control) with 120 cases of cardiovascular IgG4-RD. Most of the cases were male, averaging 62.8 years. The common initial symptoms were dyspnea and chest pain. The most common imaging finding was vasculopathy, including vessel wall thickening, periarteritits, periaortitis, aortitis, stenosis, ectasia, aneurysm formation, intramural hemorrhage, fistula formation, and dissection, followed by pericardial involvement and mediastinal masses. Case series and cross-sectional studies also showed vasculopathy being the most common finding on various imaging modalities, including angiography and PET/CT, highlighting the complex pathology of IgG4-RD., Conclusion: This study evaluated current IgG4-RD articles, revealing a higher prevalence in men and vasculopathy as the most common cardiovascular complication., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

This statement from the European Association of Cardiovascular Imaging (EACVI) of the ESC aims to address the fundamental principles that guide clinical research in the field of cardiovascular imaging. It provides clinical researchers, cardiology fellows, and Ph.D. students with a condensed, updated, and practical reference document to support them in designing, implementing, and conducting imaging protocols for clinical trials. Although the present article cannot replace formal research training and mentoring, it is recommended reading for any professional interested in becoming acquainted with or participating in clinical trials involving cardiovascular imaging., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Cardiovascular diseases remain the leading cause of global mortality, underscoring the critical need for accurate and timely diagnosis. This narrative review examines the current applications and future potential of artificial intelligence (AI) and machine learning (ML) in cardiovascular imaging. We discuss the integration of these technologies across various imaging modalities, including echocardiography, computed tomography, magnetic resonance imaging, and nuclear imaging techniques. The review explores AI-assisted diagnosis in key areas such as coronary artery disease detection, valve disorders assessment, cardiomyopathy classification, arrhythmia detection, and prediction of cardiovascular events. AI demonstrates promise in improving diagnostic accuracy, efficiency, and personalized care. However, significant challenges persist, including data quality standardization, model interpretability, regulatory considerations, and clinical workflow integration. We also address the limitations of current AI applications and the ethical implications of their implementation in clinical practice. Future directions point towards advanced AI architectures, multimodal imaging integration, and applications in precision medicine and population health management. The review emphasizes the need for ongoing collaboration between clinicians, data scientists, and policymakers to realize the full potential of AI in cardiovascular imaging while ensuring ethical and equitable implementation. As the field continues to evolve, addressing these challenges will be crucial for the successful integration of AI technologies into cardiovascular care, potentially revolutionizing diagnostic capabilities and improving patient outcomes., Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Reza-Soltani et al.)

Micro-computed tomography (micro-CT) constitutes an emerging imaging technique, which can be utilized in cardiovascular medicine to study in-detail the microstructure of heart and vessels. This paper aims to systematically review the clinical utility of micro-CT in cardiovascular imaging and propose future applications of micro-CT imaging in cardiovascular research. A systematic scoping review was conducted by searching for original studies written in English according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews. Medline, Scopus, ClinicalTrials.gov, and the Cochrane library were systematically searched through December 11, 2020 to identify publications concerning micro-CT applications in cardiovascular imaging. Preclinical-animal studies and case reports were excluded. The Newcastle-Ottawa assessment scale for observational studies was used to evaluate study quality. In total, the search strategy identified 30 studies that report on micro-CT–based cardiovascular imaging and satisfy our eligibility criteria. Across all included studies, the total number of micro-CT scanned specimens was 1,227. Six studies involved postmortem 3D-reconstruction of congenital heart defects, while eleven studies described atherosclerotic vessel (coronary or carotid) characteristics. Thirteen other studies employed micro-CT for the assessment of medical devices (mainly stents or prosthetic valves). In conclusion, micro-CT is a novel imaging modality, effectively adapted for the 3D visualization and analysis of cardiac soft tissues and devices at high spatial resolution. Its increasing use could make significant contributions to our improved understanding of the histopathophysiology of cardiovascular diseases, and, thus, has the potential to optimize interventional procedures and technologies, and ultimately improve patient outcomes.

A growing number of artificial intelligence (AI)-based systems are being proposed and developed in cardiology, driven by the increasing need to deal with the vast amount of clinical and imaging data with the ultimate aim of advancing patient care, diagnosis and prognostication. However, there is a critical gap between the development and clinical deployment of AI tools. A key consideration for implementing AI tools into real-life clinical practice is their “trustworthiness” by end-users. Namely, we must ensure that AI systems can be trusted and adopted by all parties involved, including clinicians and patients. Here we provide a summary of the concepts involved in developing a “trustworthy AI system.” We describe the main risks of AI applications and potential mitigation techniques for the wider application of these promising techniques in the context of cardiovascular imaging. Finally, we show why trustworthy AI concepts are important governing forces of AI development.

Recently, medical radiology has undergone significant improvements in patient management due to advancements in image acquisition by the last generation of machines, data processing, and the integration of artificial intelligence. In this way, cardiovascular imaging is one of the fastest-growing radiological subspecialties. In this study, a compressive review was focused on addressing how and why CT and MR have gained a I class indication in most cardiovascular diseases, and the potential impact of tissue and functional characterization by CT photon counting, quantitative MR mapping, and 4-D flow. Regarding rectal imaging, advances in cancer imaging using diffusion-weighted MRI sequences for identifying residual disease after neoadjuvant chemoradiotherapy and [18F] FDG PET/MRI were provided for high-resolution anatomical and functional data in oncological patients. The results present a large overview of the approach to the imaging of diffuse and focal liver diseases by US elastography, contrast-enhanced US, quantitative MRI, and CT for patient risk stratification. Italy is currently riding the wave of these improvements. The development of large networks will be crucial to create high-quality databases for patient-centered precision medicine using artificial intelligence. Dedicated radiologists with specific training and a close relationship with the referring clinicians will be essential human factors.